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Record W2148937411

Trainee science teachers' ideas about environmental problems caused by vehicle emissions

2010· article· en· W2148937411 on OpenAlexaboutno aff
Emine Selcen Darçın

Bibliographic record

VenueAsia-Pacific Forum on Science Learning and Teaching · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Education and Sustainability
Canadian institutionsnot available
Fundersnot available
KeywordsGlobal warmingQuarter (Canadian coin)Environmental educationGreenhouse gasGreenhouse effectSample (material)Mathematics educationEnvironmental sciencePsychologyGeographyPedagogyClimate changeChemistry
DOInot available

Abstract

fetched live from OpenAlex

The purpose of this study was to determine students’ knowledge level and misconceptions about cars and environment. The sample group of this study consists of randomly selected students from Science Education Department of Gazi Education Faculty in Turkey. The measure is applied to total of 298 students where 174 of them are female and 124 are male. According to the results the majority of the students correctly realized that car emissions contribute to the greenhouse effect and acid rain; however they have some well-known misconceptions about the mechanism by which this occurs. A quarter of the students who saw cars as a source of global warming accept that this might happen via chlorofluorocarbons (CFCs). The major misconception, held by more than two-fifth of the students who realized that cars increase global warming, is that heat from car exhaust causes

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.005
GPT teacher head0.249
Teacher spread0.245 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2010
Admission routes1
Has abstractyes

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